Dynamic voting schemes to enhance evolutionary repair in reconfigurable logic devices

Success has been demonstrated previously in the use of genetic algorithms (GAs) for autonomous fault-handling in field programmable gate array (FPGA) devices, yet the completeness of a given repair can be improved. This research explores extensions to voting systems to work in parallel with imperfect GA solutions for local permanent damage faults in the FPGA fabric. The benefits are evaluated by comparing performance with a GA that does not utilize voting, for triplex and 5-plex voting arrangements. Results indicate that recovery capability is significantly improved achieving complete repair by a process of synthesis from the incomplete repairs obtained by the GAs. Voting-enhanced systems are shown to increase the likelihood of finding a complete repair, with increases in speed and efficiency. The triplex and 5-plex voting schemes are able to find a complete repair after an average of 113.86 and 48.33 generations respectively in situations where standalone GAs consistently fail.